The uses of byproducts such as blastfurnace slag and steel slag [electric arc furnace slag and basic oxygen steel (BOS) slag, and ground granulated blastfurnace slag] have long been established in a number of applications in the civil engineering industry. However, the use of ground BOS slag fines in the area of soil stabilization has not been fully investigated and developed despite having similar chemical composition and mineralogy to that of Portland cement. This paper describes a laboratory investigation for English China clay and Mercia mudstone, which are stabilized with three BOS slag fines from three different steel production sites in the United Kingdom. The investigation also included using mixture of BOS slag fines and two different activators: quicklime and sodium metasilicate. The results indicate that the use of BOS slag fines produce improvements in strength and durability, and also reduction in expansion. However, to achieve significant improvements in strength soils required a high percen...

Plastic represents an environmental issue, as only 7% of it is recycled. The plastic remaining is either burned, disposed of in an uncontrolled manner, or landfilled. Thus, to reduce the quantity of plastic that is disposed of, there is a need to increase the amount of the material that enters various product streams. This includes its use in the construction industry, and more particularly in concrete, which uses large quantities of aggregate. A novel aggregate (RPA) comprising recycled plastic was developed. The aggregate produced was lightweight, with a density ranging from 510 to 750k kg/m3 and absorption of from 2.7 to 9.81%. Other properties were comparable to aggregates of similar densities. Various composition RPA was used in concrete, and the resulting properties of both fresh and cured concrete were measured. For a given water to cement (w/c) ratio, it was possible to achieve slump of between 40 and 220 mm and fresh density of between 1,827 and 2,055 kg/m3. Further, 28-day strengths of...

The measurement of road roughness is important for the management of economic road maintenance. Not only is it an indicator of road condition and ride quality, but it also is used to determine road use costs, including travel time, fuel consumption, and vehicle maintenance. Because of the importance of roughness for road asset management decision-making, road agencies spend considerable resources trying to measure road roughness in a repeatable and reproducible manner. However, many road agencies with large road networks are unable to record the condition of the entire network on a sufficiently frequent basis to determine adequately road condition to make informed preventative maintenance decisions. To address this, research has been carried out to develop low cost smartphone based technologies fitted inside vehicles to measure road condition. The trial of these systems has met with varying degrees of success. This paper presents an in-depth parametric study carried out using state-of-the-art vehicle dynamics software, informed by a review of the literature, to appreciate how and to what degree various influencing variables might affect roughness measurements using a smartphone fitted to a moving vehicle. These variables included the type and position of the smartphone; the type, speed, mass, dynamic response, suspension system, and tire pressure of the vehicle in which the smartphone is fitted; and the longitudinal road profile. The results of the parametric analysis were used to build multivariate linear regression and machine learning algorithms which predict road roughness from a measure of a vehicle’s vertical acceleration taking into account the predominant influencing variables. The multivariate linear regression equations can be used to predict road roughness with a similar degree of accuracy that is expected from a visual inspection. On the other hand, the machine learning algorithms, when suitably trained, were able to estimate reliably the road roughness on an integer-based rating scale at a level of detail which is suitable for strategic road asset management, provided that the vehicle type and speed and the type of smartphone are taken into account.

The effect of randomly oriented discrete synthetic fiber inclusions on the properties of soils treated with proprietary liquid chemical stabilization additives was evaluated in a laboratory-based investigation. Mercia mudstone, Oxford clay, and limestone quarry fines were stabilized with a proprietary polymer and reinforced with discrete fibers. The findings were compared with untreated and reinforced specimens, which served as the control. Test results showed that the inclusion of randomly oriented discrete synthetic fibers had no significant effect on the compaction characteristics of the soils examined. However, it did result in significant improvements in the toughness of all soils examined and load retention after peak strength for Mercia mudstone and Oxford clay. Polymer/sulphonated oil-stabilized and fiber-reinforced Mercia mudstone and Oxford clay specimens were found to be highly susceptible to moisture, while polymer-stabilized and reinforced limestone quarry fines specimens demonstrated...